Senior Applied Scientist, Alexa AI Full-time

The Alexa AI team is seeking a talented, self-driven Senior Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI.

Key job responsibilities

– Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI.

– Collaborate with cross-functional teams to architect and execute technically rigorous AI projects.

– Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines.

– Engage in effective technical communication (written & spoken) with coordination across teams.

– Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility.

– Publish research papers in internal and external venues of repute

– Support on-call activities for critical issues

A day in the life

This Senior Applied Scientist will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions in LLMs. They will also collaborate with partner teams across roles (product/program managers, data annotators, developers, etc) to deliver robust models in production.

They will mentor other scientists, review and guide their work, and help develop roadmaps for the team. They will work closely with partner teams to deliver platform features that require cross-team leadership.

BASIC QUALIFICATIONS

– PhD, or Master’s degree

– 5+ years of building machine learning models or developing algorithms for business application experience

– Experience with neural deep learning methods and machine learning

– Experience in applied research

PREFERRED QUALIFICATIONS

– PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field

– Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)

– Track record of diving into data to discover hidden patterns and conducting error/deviation analysis

– Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations

– Motivation to achieve results in a fast-paced environment.

– Exceptional level of organization and strong attention to detail

– Comfortable working in a fast paced, highly collaborative, dynamic work environment